Method Research In Uncertain Multiple Attribute Decision Making With Preference Information

Multi-attribute decision-making is the main content of Modern Decision Analysis, and their essence is to rank the alternatives and choose the best alter-native under many criteria. In general, multi-attribute decision-making contains plenty of fuzzy information or uncertain information. There are lots of uncertain multi-attribute decision-making problems. This paper mainly deals with the un-certain multi-attribute decision-making problems with preference information. It consists of four chapters.In the first chapter, we mainly introduce the development and current re-search situations of the uncertain multi-attribute decision-making problems. Fur-thermore, we list the main contribution of this paper.In the second chapter, Intuitionistic Trapezoidal Fuzzy Multi-criteria Deci-sion Making with preference to alternative are investigated, a programming modal is introduced to assess the weights of attributes, which integrates subjective fuzzy preference relations and objective information. And a numerical example is given to show the feasibility and effectiveness of the developed methodIn the third chapter, studied was multiple attribute decision making, in which the information about attribute weights is unknown completely and the attribute values and preference information on alternatives take the form of uncertain lin-guistic variables. Operational laws of uncertain linguistics variables were intro-duced. The concept of deviation degree between uncertain linguistic variables was developed. A programming modal is introduced to assess the weights of attributes, which integrates subjective fuzzy preference relations and objective information. The uncertain linguistic weighting average(ULWA) operator was utilized to aggregate the uncertain linguistics variables corresponding to each alternative. A possibility degree matrix was constructed by the formula of pos-sibility degree. The alternatives were ranked by using the priority formula of complementary judgement matrixes and the most desirable one was selected. An illustrative example is given to highlighe the procedure of the proposed algorithm.In the last chapter, a mutiple-criteria ranking method is proposed in which the information on the criteria weights is incomplete certain and criteria's values is interval intuitionistic fuzzy set. The formula for measuring the distance be-tween interval-valued intuitionistic fuzzy numbers is given and the concepts int of erval-valued intuitionistic fuzzy positive-ideal point and interval-valued intuition-istic fuzzy negative-ideal point are defined. The distances between alternatives and idea/anti-idea alternatives are computed. Considering the incomplete cer-tain information on weights, a linear programming modal is developed. By using matlab to solve the linear programming models, the optimal criteria's weights are gained, and ranking is performed through the comparision of the distances be-tween the alternatives and idea/anti-idea alternative. Finally, an example shows the feasibility and availability of this method.